Cassandra also places a high value on performance. In 2012, University of Toronto researchers studying NoSQL systems concluded that "In terms of scalability, there is a clear winner throughout our experiments. Cassandra achieves the highest throughput for the maximum number of nodes in all experiments" although "this comes at the price of high write and read latencies."[2]

Avinash Lakshman (one of the authors of Amazon's Dynamo) and Prashant Malik initially developed Cassandra at Facebook to power the Facebook inbox search feature. Facebook released Cassandra as an open-source project on Google code in July 2008.[3] In March 2009 it became an Apache Incubator project.[4] On February 17, 2010 it graduated to a top-level project.[5]

Facebook developers named their database after the Trojan mythological prophet Cassandra - with classical allusions to a curse on an oracle.[6]

3.0 releases and later will be monthly releases using a tick-tock-like release model, with even-numbered releases providing both new features and bug fixes while odd-numbered releases will include bug fixes only.[15]

Every node in the cluster has the same role. There is no single point of failure. Data is distributed across the cluster (so each node contains different data), but there is no master as every node can service any request.

Supports replication and multi data center replication

Replication strategies are configurable.[17] Cassandra is designed as a distributed system, for deployment of large numbers of nodes across multiple data centers. Key features of Cassandra’s distributed architecture are specifically tailored for multiple-data center deployment, for redundancy, for failover and disaster recovery.

Scalability

Read and write throughput both increase linearly as new machines are added, with no downtime or interruption to applications.

Fault-tolerant

Data is automatically replicated to multiple nodes for fault-tolerance. Replication across multiple data centers is supported. Failed nodes can be replaced with no downtime.

Tunable consistency

Writes and reads offer a tunable level of consistency, all the way from "writes never fail" to "block for all replicas to be readable", with the quorum level in the middle.[18]

Cassandra introduced the Cassandra Query Language (CQL). CQL is a simple interface for accessing Cassandra, as an alternative to the traditional Structured Query Language (SQL). CQL adds an abstraction layer that hides implementation details of this structure and provides native syntaxes for collections and other common encodings.[20] Language drivers are available for Java (JDBC), Python (DBAPI2), Node.JS (Helenus), Go (gocql) and C++.[21]

Below an example of keyspace creation, including a column family in CQL 3.0:[22]

Cassandra is essentially a hybrid between a key-value and a column-oriented (or tabular) database management system. Its data model is a partitioned row store with tunable consistency.[18] Rows are organized into tables; the first component of a table's primary key is the partition key; within a partition, rows are clustered by the remaining columns of the key.[24] Other columns may be indexed separately from the primary key.[25]

Tables may be created, dropped, and altered at run-time without blocking updates and queries.[26]

A column family (called "table" since CQL 3) resembles a table in an RDBMS. Column families contain rows and columns. Each row is uniquely identified by a row key. Each row has multiple columns, each of which has a name, value, and a timestamp. Unlike a table in an RDBMS, different rows in the same column family do not have to share the same set of columns, and a column may be added to one or multiple rows at any time.[28]

Each key in Cassandra corresponds to a value which is an object. Each key has values as columns, and columns are grouped together into sets called column families. Thus, each key identifies a row of a variable number of elements. These column families could be considered then as tables. A table in Cassandra is a distributed multi dimensional map indexed by a key. Furthermore, applications can specify the sort order of columns within a Super Column or Simple Column family.

When the cluster for Apache Cassandra is designed, an important point is to select the right partitioner. Two partitioners exist:[29]

OrderPreservingPartitioner (OPP): This partitioner distributes the key-value pairs in a natural way so that similar keys are not far away. The advantage is that fewer nodes have to be accessed. The drawback is the uneven distribution of the key-value pairs.

RandomPartitioner (RP): This partitioner randomly distributes the key-value pairs over the network, resulting in a good load balancing. Compared to OPP, more nodes have to be accessed to get a number of keys.

Cassandra is a Java-based system that can be managed and monitored via Java Management Extensions (JMX). The JMX-compliant nodetool utility, for instance, can be used to manage a Cassandra cluster (adding nodes to a ring, draining nodes, decommissioning nodes, and so on).[30] Nodetool also offers a number of commands to return Cassandra metrics pertaining to disk usage, latency, compaction, garbage collection, and more.[31] Additional metrics are available via JMX tools such as JConsole and via pluggable metrics reporters for external monitoring tools, which became available with Cassandra version 2.0.2.[32]

Cloudkick uses Cassandra to store the server metrics of their users.[42]

Constant Contact uses Cassandra in their email and social media marketing applications.[43] Over 200 nodes are deployed.

Digg, a large social news website, announced on Sep 9th, 2009 that it is rolling out its use of Cassandra[44] and confirmed this on March 8, 2010.[45]TechCrunch has since linked Cassandra to Digg v4 reliability criticisms and recent company struggles.[46] Lead engineers at Digg later rebuked these criticisms as red herring and blamed a lack of load testing.[47]

Facebook used Cassandra to power Inbox Search, with over 200 nodes deployed.[48] This was abandoned in late 2010 when they built Facebook Messaging platform on HBase as they "found Cassandra's eventual consistency model to be a difficult pattern".[49] Facebook moved off its pre-Apache Cassandra deployment in late 2010 when they replaced Inbox Search with the Facebook Messaging platform.[49] In 2012, Facebook began using Apache Cassandra in its Instagram unit.[50]

Formspring uses Cassandra to count responses, as well as store Social Graph data (followers, following, blockers, blocking) for 26 Million accounts with 10 million responses a day[51]

IBM has done research in building a scalable email system based on Cassandra.[52]

Mahalo.com uses Cassandra to record user activity logs and topics for their Q&A website[53][54]

Netflix uses Cassandra as their back-end database for their streaming services[55][56]

Ooyala built a scalable, flexible, real-time analytics engine using Cassandra[58]

Openwave uses Cassandra as a distributed database and as a distributed storage mechanism for their next generation messaging platform[59]

OpenX is running over 130 nodes on Cassandra for their OpenX Enterprise product to store and replicate advertisements and targeting data for ad delivery[60]

Plaxo has "reviewed 3 billion contacts in [their] database, compared them with publicly available data sources, and identified approximately 600 million unique people with contact info."[61]

Plexistor for Apache Cassandra delivers high capacity storage at near-memory speed, reducing the need for expensive memory and dedicated servers. Plexistor can be used in Amazon AWS as well as on premise, running on Linux OS or on Docker containers.[62]

^Casares, Joaquin (2012-11-05). "Multi-datacenter Replication in Cassandra". DataStax. Retrieved 2013-07-25. Cassandra’s innate datacenter concepts are important as they allow multiple workloads to be run across multiple datacenters…

^Rabl, Tilmann; Sadoghi, Mohammad; Jacobsen, Hans-Arno; Villamor, Sergio Gomez-; Mulero -, Victor Muntes; Mankovskii, Serge (2012-08-27). "Solving Big Data Challenges for Enterprise Application Performance Management"(PDF). VLDB. Retrieved 2013-07-25. In terms of scalability, there is a clear winner throughout our experiments. Cassandra achieves the highest throughput for the maximum number of nodes in all experiments... this comes at the price of high write and read latencies

^"The meaning behind the name of Apache Cassandra". Retrieved 2016-07-19. Apache Cassandra is named after the Greek mythological prophet Cassandra. [...] Because of her beauty Apollo granted her the ability of prophecy. [...] When Cassandra of Troy refused Apollo, he put a curse on her so that all of her and her descendants' predictions would not be believed. [...] Cassandra is the cursed Oracle[.]

^Williams, Dominic. "Cassandra: RandomPartitioner vs OrderPreservingPartitioner". http://wordpress.com/: WordPress.com. Retrieved 2011-03-23. When building a Cassandra cluster, the “key” question (sorry, that’s weak) is whether to use the RandomPartitioner (RP), or the OrdengPartitioner (OPP). These control how your data is distributed over your nodes. Once you have chosen your partitioner, you cannot change without wiping your data, so think carefully! The problem with OPP: If the distribution of keys used by individual column families is different, their sets of keys will not fall evenly across the ranges assigned to nodes. Thus nodes will end up storing preponderances of keys (and the associated data) corresponding to one column family or another. If as is likely column families store differing quantities of data with their keys, or store data accessed according to differing usage patterns, then some nodes will end up with disproportionately more data than others, or serving more “hot” data than others.